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小波变换在测井曲线识别划分岩性中的应用
首发时间：2019-05-10
摘要：测井曲线包含了丰富的地质信息，对研究地层、识别岩性具有很大的优势。为此，引入小波变换多尺度分析的思想，对测井数据进行时频分析。本文以芦岭矿区l43井测井数据为样本，选取视电阻率（lld）、自然伽马（gr）、声波时差（ac）、密度(den)测井数据，进行小波变换处理。结果表明，对于此区，选用sym8小波基，7级分解后，重构测井曲线，对选段岩性响应最为明显。煤层表现为两高（高ac值，高lld值）、两低（低den值，低gr值）特征，泥岩表现为两高（高den值，高gr值）特征。基于测井曲线小波变换的岩性识别方法，提高了测井曲线纵向分辨率，提高了岩性识别的可靠性。
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application of wavelet transform in lithology identification of logging curve
abstract：well logs contain rich geological information, which has great advantages in studying strata and identifying lithology. therefore, the idea of multi-scale analysis based on wavelet transform is introduced to time-frequency analysis of well logs. this paper takes logging data of well l43 in luling mining area as samples, selects log data of apparent resistivity (lld), natural gamma (gr), acoustic time difference (ac) and density (den) for wavelet transform processing. the results show that the sym8 wavelet application of wavelet transform in lithology identification of logging curvebase is chosen to reconstruct the log curve, and the response to the selected section lithology is the most obvious. the coal seam is characterized by two high (high ac value, high lld value) and two low (low den value, low gr value), and the mudstone is characterized by two high (high den value, high gr value). the lithology identification method based on logging curve wavelet transform improves the longitudinal resolution of logging curve and the reliability of lithology identification.
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小波变换在测井曲线识别划分岩性中的应用
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